CN111462827A - Quantitative prediction method for estrogen interference activity based on nuclear receptor dimerization process - Google Patents
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Abstract
The invention discloses a quantitative prediction method for estrogen interference activity based on a nuclear receptor dimerization process, and belongs to the field of toxicology prediction. Firstly, obtaining a crystal structure of an estrogen receptor, determining an estrogen effect EC50 value of a ligand in the crystal structure, and then preprocessing a receptor protein and a ligand molecule of the crystal structure of the estrogen receptor; then constructing a complex to perform molecular dynamics simulation on the complex, and calculating the free binding energy of the complex; establishing a quantitative correlation relationship, and fitting a regression prediction model; and finally, predicting the estrogen interference activity by using the fitted regression model. The invention comprehensively considers the processes of ligand binding, dimerization and cofactor recruitment, then calculates the binding energy of the complex by using a molecular dynamics method, and establishes a prediction regression model, thereby effectively improving the prediction accuracy of the estrogen interference activity.
Description
Technical Field
The invention belongs to the field of toxicology prediction, and particularly relates to a quantitative prediction method for estrogen interference activity based on a nuclear receptor dimerization process.
Background
Endocrine Disrupting Chemicals (EDCs) refer to substances that interfere with the endocrine system of humans or animals and cause adverse health effects. Since EDCs are widely detected in the environment and human body, exposure to endocrine-interfering substances not only causes a series of adverse health effects but also causes huge economic losses, disease treatment in the European Union due to EDCs costs 2170 billion dollars, which accounts for 1.28% of the total domestic production value, whereas the U.S. value amounts to 3400 billion dollars, which accounts for 2.33% of the total domestic production value. Thus, the identification and control of EDCs has been a hot spot in the research of the world environmental health and safety field.
The main action path of the EDCs is to combine with hormone receptors in cell nucleus and change the function of the hormone receptors, thereby causing interference effect, and the estrogen interferents have a large potential relation with diseases such as reproductive diseases, birth defects, breast cancer and the like, so the estrogen receptors become widely concerned receptors in research on the EDCs, for example, the EDCs can generate a pseudo-female effect or an anti-female effect through the estrogen receptor α (estrogen receptor α α), the pseudo-female effect can cause the breast cancer, and the anti-estrogen effect can cause the reproductive disorder.
In the prior art, there are many methods for screening or predicting EDCs by computer assistance, for example, the application numbers are: 200810123727.3 discloses a method for identifying the agonistic and antagonistic action of organic estrogen receptors; the Chinese patent with the application number of 201310288617.3 discloses a virtual screening method of nuclear receptor mediated endocrine disrupting substances based on molecular dynamics simulation; chinese patent application No. 201610201950.X discloses a thyroid hormone interferent virtual screening method based on nuclear receptor coregulator and a quantitative calculation method of interference activity of the thyroid hormone interferent virtual screening method. Estrogen Receptors (ERs) belong to ligand-dependent transcription factors whose activity is highly dependent on ligand binding, and once inside the nucleus, ERs bind to specific genomic DNA response elements in the form of homo-or heterodimers, thereby activating or inhibiting transcription by recruiting cofactors and other transcription factors to form transcription regulatory complexes. Dimer formation is thought to be essential for normal receptor function, and mutations that interfere with dimer formation result in transcriptional inactivation of the receptor. Dimerization is affected by the binding of chemical substances to nuclear receptors, and the stability of the dimer reflects not only the affinity of the ligand for the receptor, but also the properties of the ligand itself. Because of the importance of nuclear receptors in DNA binding and transcriptional regulation, dimerization is a feature of EDCs screening.
In the existing research, there are two main aspects of the dimerization process, one is in vitro experiment (low throughput, time and labor consuming) and one is simulation research, but most of the current simulation is directed to monomer research mainly because the step of recruiting cofactors is considered to be more important, so the dimerization process is often ignored in the simulation process. In addition, the existing analog research on the dimer is mostly based on an unfolded structure which is not the initial state of ER, the system is large, the process is complex, and a plurality of factors need to be considered; and the dimer-based research mainly aims at analyzing the influence of the process on H12 (the ER receptor structure has 12 helices, and the 12 th helix H12 is important for judging the quasi-anti effect of a substance), and the interference activity of estrogen is difficult to predict. Therefore, in the prior art, the prediction method for the estrogen interference activity is to establish a prediction model by utilizing ligand receptor binding and cofactor recruitment process aiming at the quasi or resistance effect in the form of taking a nuclear receptor as a monomer, and the dimerization process after the combination of the EDCs and the receptor is not fully considered, so that the accuracy is lower when the prior method is used for predicting the estrogen interference activity.
Disclosure of Invention
The technical problem is as follows: the invention provides a quantitative prediction method for estrogen interference activity based on a nuclear receptor dimerization process, which predicts the estrogen interference activity of endocrine interfering substances on the basis of comprehensively considering the processes of ligand receptor combination, dimerization and co-factor recruitment, and improves the accuracy of prediction.
The technical scheme is as follows: the invention relates to a quantitative prediction method of estrogen interference activity based on a nuclear receptor dimerization process, which is characterized by comprising the following steps:
s1: acquiring a crystal structure of an estrogen receptor, and determining an estrogen effect EC50 value of a ligand in the crystal structure;
s2: pretreating a receptor protein and a ligand molecule of a crystal structure of an estrogen receptor;
s3: constructing an estrogen receptor dimer-ligand complex and an estrogen receptor dimer-ligand-cofactor complex, respectively performing molecular dynamics simulation on each complex, extracting a plurality of conformations from a molecular dynamics simulation track, and calculating the free binding energy of each complex;
s4: respectively establishing a quantitative correlation relationship between the free binding energy of an estrogen receptor dimer-ligand complex and the free binding energy of the estrogen receptor dimer-ligand-cofactor complex and an estrogen effect EC50 value, and fitting a corresponding regression prediction model;
s5: and (3) utilizing the regression prediction model and utilizing molecular dynamics simulation to obtain a value of free binding energy so as to predict the estrogen interference activity.
Further, in step S2, the method for preprocessing the receptor protein with the crystal structure of the estrogen receptor includes:
firstly, checking the integrity of a crystal structure, completely supplementing the incomplete amino acid residues, and then carrying out hydrotreatment on the crystal structure;
the following structures are respectively extracted from the crystal structure after treatment: (1) extracting an estrogen receptor dimer, wherein the estrogen receptor dimer comprises a monomer 1 and a monomer 2;
(2) extracting a complex of an estrogen receptor dimer and a cofactor, wherein the complex comprises a monomer 1, a monomer 2, a cofactor 1 and a cofactor 2;
(3) extracting the ligand, wherein the ligand comprises a ligand 1 and a ligand 2, and the ligand 1 and the ligand 2 are respectively extracted.
Further, in step S2, the method for pre-treating the ligand molecules includes: the extracted ligand is hydrotreated and a force field is imparted to the ligand.
Further, in step S3, constructing an estrogen receptor dimer-ligand complex by using the pretreated ligand and an estrogen receptor dimer, wherein the estrogen receptor dimer-ligand complex includes monomer 1, monomer 2, ligand 1 and ligand 2;
and constructing an estrogen receptor dimer-ligand-cofactor complex by using the estrogen receptor dimer and cofactor complex and the pretreated ligand, wherein the estrogen receptor dimer-ligand-cofactor complex comprises a monomer 1, a monomer 2, a ligand 1, a ligand 2, a cofactor 1 and a cofactor 2.
Further, in step S3, performing molecular dynamics simulation on the complex by using GROMACS software, the specific method is as follows:
s3.1: imparting a CHARMM force field to the receptor protein;
s3.2: immersing the complex in TIP3P model water, wherein the distance from the edge of the complex to the edge of the water layer is more than or equal to 1.4nm, and adding sodium ions or chloride ions to balance the charge of the system;
s3.3: performing energy minimization by adopting a gradient descent method, and further balancing a system through two-step balance simulation of an NVT ensemble and an NPT ensemble;
and S3.4, setting a simulation environment and simulation time, calculating the remote electric interaction by adopting a PME method, carrying out bond constraint by adopting an L INCS method, and then completing molecular dynamics simulation.
Further, in step S3, the free binding energy of the complex is calculated by using a molecular mechanics-poisson boltzmann surface area method.
Further, the method for calculating the free binding energy of the estrogen receptor dimer-ligand complex is: calculation of free binding energy Δ G between monomer 1 and ligand 1Monomer 1Calculating the free binding energy Δ G between monomer 2 and ligand 2Monomer 2Free binding energy of the Estrogen receptor dimer-ligand Complex Δ GDimer＝ΔGMonomer 1+ΔGMonomer 2；
The method for calculating the free binding energy of the estrogen receptor dimer-ligand-cofactor complex is as follows: calculation of free binding energy Δ G between monomer 1, ligand 1 and cofactor 1Monomeric 1-cofactor 1Calculating the free binding energy delta G among the monomer 2, the ligand 2 and the cofactor 2Monomeric 2-cofactor 2Free binding energy of estrogen receptor dimer-ligand-co-factor complex Δ GDimer-cofactors＝ΔGMonomeric 1-cofactor 1+ΔGMonomeric 2-cofactor 2。
Further, in step S4, the regression prediction model is determined to have the form:
-logEC50＝a+kΔG
wherein log (EC50) represents the logarithm of EC50 value, a and k are coefficients, and Δ G represents free binding energy.
Further, in step S1, the collected estrogen receptors have a crystal structure in a dimer form and a resolution of 2.4 angstrom or less.
Further, in step S2, Swiss-PdbViewer software is used to check the integrity of the crystal structure, and PyMO L software is used to hydrotreat the crystal structure.
Has the advantages that: compared with the prior art, the invention has the following advantages:
(1) in the prior art, only the ligand-receptor binding and co-factor recruitment processes are considered, and the accuracy of prediction of estrogen interference effect is low due to unclear estrogen mechanism.
(2) Compared with the traditional in-vitro experiment method, the method disclosed by the invention is low in cost and high in efficiency.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a block diagram of an ER α dimer-ligand complex in accordance with an embodiment of the present invention;
FIG. 3 is a graph of the quantitative relationship between free binding energy of ER α dimer-ligand complex and-logEC 50 value in an example of the present invention;
FIG. 4 is a block diagram of the ER α dimer-ligand-cofactor complex in an embodiment of the present invention;
FIG. 5 is a graph of the quantitative relationship between the free binding energy of the ER α dimer-ligand-cofactor complex and the-logEC 50 value in accordance with an embodiment of the present invention;
FIG. 6 is a block diagram of ER α monomer-ligand in an embodiment of the present invention;
FIG. 7 is a graph of the quantitative relationship of free binding energy of ER α monomer-ligand complexes to-logEC 50 values in an example of the invention;
FIG. 8 is a block diagram of ER α monomer-ligand-cofactor in an embodiment of the present invention;
FIG. 9 is a graph of the quantitative relationship between free binding energy of ER α monomer-ligand-cofactor complexes and-logEC 50 values in examples of the present invention.
Detailed Description
The invention is further described with reference to the following examples and the accompanying drawings.
Example 1
The estrogen receptor used in this example is the estrogen receptor α (estrogen receptor α α), and the estrogen receptor α is hereinafter referred to as ER α, and it is to be noted that the estrogen receptor of the present invention is not limited to ER α.
The method of the present invention is illustrated with reference to FIG. 1. obtaining the crystal structure of ER α, in this example, the crystal structure of ER α is searched and downloaded from RCSB Protein Data Bank (http:// www.rcsb.org/pdb/home. do), the crystal structure of ER α is downloaded in a dimer form with a resolution of 2.4 angstroms or less, and the values of EC50 and EC50, which have been reported to determine the estrogen effect of the corresponding ligand of the downloaded ER α crystal structure, can be used to show the interfering activity of estrogen.
TABLE 1 ER α Crystal Structure and Estrogen Effect EC50 and-logEC 50 values of the corresponding ligands
The ER α dimer consists of two monomers, referred to herein for ease of illustration as monomer 1 and monomer 2, each monomer corresponding to a ligand and a cofactor, thus monomer 1 corresponding to ligand 1 and cofactor 1, and monomer 2 corresponding to ligand 2 and cofactor 2 the resulting receptor protein of the ER α crystal structure is pre-treated by first examining the integrity of the crystal structure using Swiss-PdbViewer software and complementing the missing amino acid residues to integrity, then hydrotreating the crystal structure using PyMO L software, followed by the respective extraction of the following structures:
(1) extracting ER α dimer of ER α, wherein the ER α dimer comprises two monomers, namely monomer 1 and monomer 2;
(2) extracting a complex of an ER α dimer and a cofactor, so that the complex comprises two monomers and two cofactors, namely monomer 1, monomer 2, cofactor 1 and cofactor 2;
(3) extracting ligands, wherein each monomer has a corresponding ligand, and in the specific operation, the corresponding ligand of each monomer is respectively extracted and respectively stored, and when the operation is carried out by adopting software, the ligand 1 is stored as the ligand 1. pdb; ligand 2 was saved as ligand 2. pdb.
After the ligand is extracted, the ligand molecules are pretreated, and the pretreatment method comprises the following steps: the extracted ligand is hydrotreated and a force field is imparted to the ligand. In specific operation through software, firstly, the file ligand 1.pdb and ligand 2.pdb are opened by using Open Babel software, the ligand 1 and ligand 2 are hydrotreated, then the file is converted into a. mol2 format file to be stored, namely the ligand 1.mol2 and the ligand 2.mol2, and then the Swiss-Param is used for endowing a ligand force field.
After the pretreatment is completed, an ER α dimer-ligand complex is constructed, specifically, an ER α dimer-ligand complex is constructed by using the pretreated ligand and an ER α dimer, so that the constructed ER α dimer-ligand complex comprises an ER α dimer and a ligand 1 and a ligand 2, namely a monomer 1, a monomer 2, a ligand 1 and a ligand 2, and the structure of the ER α dimer-ligand complex is shown in FIG. 2.
The ER α dimer-ligand-cofactor complex is constructed, specifically, the ER α dimer-ligand-cofactor complex is constructed by using the pretreated ligand and ER α dimer and cofactor complex, so that the complex comprises monomer 1, monomer 2, ligand 1, ligand 2, cofactor 1 and cofactor 2, and the structure of the ER α dimer-ligand-cofactor complex is shown in FIG. 4.
Molecular dynamics simulation was performed on each of the constructed ER α dimer-ligand complex and the ER α dimer-ligand-co-factor complex, and in this example, GROMACS software was used to perform the molecular dynamics simulation.
S3.1: the CHARMM force field is imparted to the receptor protein, and in particular manipulations, the CHARMM 27 force field is selected. Because the ligand has been given a force field when it was pre-processed, but after ligand 1 and ligand 2 were given a force field during a particular software operation, the resulting topology file includes atomtype and pacifypes portions, which need to be merged at the time of the particular operation.
S3.2: the complex was immersed in TIP3P model water, where the distance from the edge of the complex to the edge of the water layer was greater than or equal to 1.4nm, which was set to 1.4nm in this example, and sodium or chloride ions were added to balance the charge of the system.
S3.3: and (3) minimizing energy by adopting a gradient descent-gradient method (steady-state), and further balancing the system by a two-step balance simulation of an NVT (constant temperature and constant volume) ensemble and an NPT (constant temperature and constant pressure) system.
S3.4, setting a simulation environment and simulation time, calculating the remote electrical interaction by adopting a PME method, carrying out bond Constraint by adopting an L INCS (L inner Constraint Server, L INCS) method, and then completing the molecular dynamics simulation, wherein the simulation environment comprises atmospheric pressure and temperature, 1 standard atmospheric pressure is adopted in the embodiment, the temperature is 300K, and the simulation time is set to be 20 ns.
After all the parameters are set, the molecular dynamics simulation of the complex can be completed, and a molecular dynamics track is generated.
The molecular dynamics simulation of the ER α dimer-ligand complex and the ER α dimer-ligand-co-factor complex are respectively completed by the method, and a corresponding molecular dynamics simulation track is generated.
Wherein the free binding energy of the ER α dimer-ligand complex is calculated by calculating the free binding energy Δ G between monomer 1 and ligand 1Monomer 1Calculating the free binding energy Δ G between monomer 2 and ligand 2Monomer 2Then the free binding energy Δ G of the ER α dimer-ligand complexDimer＝ΔGMonomer 1+ΔGMonomer 2。
The free binding energy of ER α dimer-ligand-cofactor complex was calculated by calculating the free binding energy Δ G between monomer 1, ligand 1 and cofactor 1Monomeric 1-cofactor 1Calculating the free binding energy delta G among the monomer 2, the ligand 2 and the cofactor 2Monomeric 2-cofactor 2Then the free binding energy Δ G of the estrogen receptor dimer-ligand-co-factor complexDimer-cofactors＝ΔGMonomeric 1-cofactor 1+ΔGMonomeric 2-cofactor 2. The free binding energy can be directly obtained by software calculation, and is calculated by adopting a g _ mmpbsa program developed by GROMACS and APBS. In this example, specific values for the free binding energies of the two complexes are shown in table 2:
TABLE 2 free binding energy calculation of two complexes
Note: the free binding energy unit is kJ/mol.
In this example, GraphPad Prism 8.0 was used to establish the quantitative correlations and to fit the regression prediction model, which in this example, expressed the pseudo-estrogenic effect in the form of the logarithm of the EC50 value, specifically in the form of-logEC 50, thus establishing the quantitative correlations of the ER α dimer-ligand complex according to Table 2, as shown in FIG. 3, and fitting the regression prediction model as:
-logEC50＝-0.0072ΔGdimer+4.3002
Wherein, when regression fitting is performed, R2Is 0.8296.
In the same manner, a quantitative correlation of ER α dimer-ligand-cofactor complex was established, as shown in fig. 5, and a regression prediction model was fitted as:
-logEC50＝-0.0073ΔGdimer-cofactors+4.1913
Wherein R is2Is 0.8338.
According to the fitted regression prediction model, the estrogen interference activity of the estrogen receptor can be predicted under the condition that the free binding energy is known.
In order to illustrate the higher accuracy of the prediction of the method of the present invention compared to the prior art, the method of the present invention was compared to the prior art, in which the prediction was performed in consideration of monomers, ligands and cofactors, in a specific method, an ER α monomer-ligand complex was constructed, the structure of which is shown in fig. 6, and a quantitative correlation of the ER α monomer-ligand complex was established, as shown in fig. 7, in combination with the data of table 2, the fitted regression prediction model was:
-logEC50＝-0.0248ΔGmonomer+2.5275
Wherein R is2Is 0.7413.
The monomer-ligand-cofactor complex is constructed, the structure is shown in fig. 8, the quantitative correlation relationship of the ER α monomer-ligand cofactor complex is established, as shown in fig. 9, and then the fitted regression prediction model is:
-logEC50＝-0.0268ΔGmonomer-cofactor+2.1759
Wherein R is2Is 0.7599.
According to R2Therefore, the fitted regression prediction model is used for predicting the estrogen interference activity, and the accuracy is better. To further illustrate the greater accuracy of the present invention over the prior art, a portion of the compounds were selected for computational comparison, as shown in table 3.
TABLE 3 comparative data for the method of the invention and the prior art methods
As can be seen from Table 3, when the method of the present invention is used for predicting the estrogen-interfering activity, the relative error between the value measured by the test and the value obtained by the prediction in the prior art is smaller than that obtained by the prediction in the prior art, thereby showing that the method of the present invention effectively improves the accuracy of the prediction in comparison with the prior art.
The invention provides an estrogen interference activity quantitative prediction method based on a nuclear receptor dimerization process, which comprehensively considers the processes of the combination of an interference substance and a nuclear receptor, dimerization, co-factor combination and the like, utilizes molecular dynamics to simulate a constructed complex, establishes a quantitative correlation relationship between an estrogen effect and free binding energy, and fits a regression prediction model. Compared with the prior art, the method has higher prediction accuracy.
The above examples are only preferred embodiments of the present invention, it should be noted that: it will be apparent to those skilled in the art that various modifications and equivalents can be made without departing from the spirit of the invention, and it is intended that all such modifications and equivalents fall within the scope of the invention as defined in the claims.
Claims (10)
1. A quantitative prediction method of estrogen interference activity based on a nuclear receptor dimerization process is characterized by comprising the following steps:
s1: acquiring a crystal structure of an estrogen receptor, and determining an estrogen effect EC50 value of a ligand in the crystal structure;
s2: pretreating a receptor protein and a ligand molecule of a crystal structure of an estrogen receptor;
s3: constructing an estrogen receptor dimer-ligand complex and an estrogen receptor dimer-ligand-cofactor complex, respectively performing molecular dynamics simulation on each complex, extracting a plurality of conformations from a molecular dynamics simulation track, and calculating the free binding energy of each complex;
s4: respectively establishing a quantitative correlation relationship between the free binding energy of an estrogen receptor dimer-ligand complex and the free binding energy of the estrogen receptor dimer-ligand-cofactor complex and an estrogen effect EC50 value, and fitting a corresponding regression prediction model;
s5: and (3) utilizing the regression prediction model and utilizing molecular dynamics simulation to obtain a value of free binding energy so as to predict the estrogen interference activity.
2. The method for quantitatively predicting estrogen interference activity based on the dimerization process of nuclear receptors according to claim 1, wherein in the step S2, the method for preprocessing the receptor protein of the crystal structure of the estrogen receptor comprises:
firstly, checking the integrity of a crystal structure, completely supplementing the incomplete amino acid residues, and then carrying out hydrotreatment on the crystal structure;
the following structures are respectively extracted from the crystal structure after treatment: (1) extracting an estrogen receptor dimer, wherein the estrogen receptor dimer comprises a monomer 1 and a monomer 2;
(2) extracting a complex of an estrogen receptor dimer and a cofactor, wherein the complex comprises a monomer 1, a monomer 2, a cofactor 1 and a cofactor 2;
(3) extracting the ligand, wherein the ligand comprises a ligand 1 and a ligand 2, and the ligand 1 and the ligand 2 are respectively extracted.
3. The method for quantitatively predicting the estrogen interference activity based on the dimerization process of the nuclear receptor according to claim 2, wherein in the step S2, the ligand molecules are pretreated by: the extracted ligand is hydrotreated and a force field is imparted to the ligand.
4. The method for quantitatively predicting estrogen interference activity based on the dimerization process of nuclear receptors according to claim 3, wherein in the step S3, the pretreated ligand and the estrogen receptor dimer are used to construct an estrogen receptor dimer-ligand complex, wherein the estrogen receptor dimer-ligand complex comprises monomer 1, monomer 2, ligand 1 and ligand 2;
and constructing an estrogen receptor dimer-ligand-cofactor complex by using the estrogen receptor dimer and cofactor complex and the pretreated ligand, wherein the estrogen receptor dimer-ligand-cofactor complex comprises a monomer 1, a monomer 2, a ligand 1, a ligand 2, a cofactor 1 and a cofactor 2.
5. The method for quantitatively predicting the estrogen-related interference activity of the nuclear receptor dimerization process as claimed in claim 4, wherein in step S3, GROMACS software is used to perform molecular dynamics simulation on the complex, which comprises:
s3.1: imparting a CHARMM force field to the receptor protein;
s3.2: immersing the complex in TIP3P model water, wherein the distance from the edge of the complex to the edge of the water layer is more than or equal to 1.4nm, and adding sodium ions or chloride ions to balance the charge of the system;
s3.3: performing energy minimization by adopting a gradient descent method, and further balancing a system through two-step balance simulation of an NVT ensemble and an NPT ensemble;
and S3.4, setting a simulation environment and simulation time, calculating the remote electric interaction by adopting a PME method, carrying out bond constraint by adopting an L INCS method, and then completing molecular dynamics simulation.
6. The method for quantitatively predicting the estrogen-related interference activity of the nuclear receptor dimerization process as claimed in claim 5, wherein in the step S3, the free binding energy of the complex is calculated by using a molecular mechanics-Poisson Boltzmann surface area method.
7. The method for quantitatively predicting the estrogen interference activity based on the dimerization process of the nuclear receptor according to claim 6, wherein the method for calculating the free binding energy of the estrogen receptor dimer-ligand complex comprises the following steps: calculation of free binding energy Δ G between monomer 1 and ligand 1Monomer 1Calculating the free binding energy Δ G between monomer 2 and ligand 2Monomer 2Free binding energy of the Estrogen receptor dimer-ligand Complex Δ GDimer＝ΔGMonomer 1+ΔGMonomer 2；
The method for calculating the free binding energy of the estrogen receptor dimer-ligand-cofactor complex is as follows: calculation of free binding energy Δ G between monomer 1, ligand 1 and cofactor 1Monomeric 1-cofactor 1Calculating the free binding energy delta G among the monomer 2, the ligand 2 and the cofactor 2Monomeric 2-cofactor 2Free binding energy of estrogen receptor dimer-ligand-co-factor complex Δ GDimer-cofactors＝ΔGMonomeric 1-cofactor 1+ΔGMonomeric 2-cofactor 2。
8. The method for quantitatively predicting the estrogen interference activity based on the dimerization process of the nuclear receptor according to any one of claims 1 to 7, wherein in the step S4, the regression prediction model is determined in the form of:
-logEC50＝a+kΔG
wherein log (EC50) represents the logarithm of EC50 value, a and k are coefficients, and Δ G represents free binding energy.
9. The method for quantitatively predicting estrogen-related activity based on dimerization process of nuclear receptors according to claim 1, wherein in step S1, the collected crystal structures of the estrogen receptors are all in dimer form and have a resolution less than or equal to 2.4 angstroms.
10. The method of claim 2, wherein in step S2, the integrity of the crystal structure is checked by Swiss-PdbViewer software, and the crystal structure is hydrotreated by PyMO L software.
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